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Approximate Classifiers with Controlled Accuracy

Demianiuk, Vitalii and Kogan, Kirill and Nikolenko, Sergey (2019) Approximate Classifiers with Controlled Accuracy. In: The 38th IEEE International Conference on Computer Communications (IEEE INFOCOM 2019), 29 Apr - 02 May 2019, Paris, France.

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Abstract

Performing exact computations can require significant resources. Approximate computing allows to alleviate resource constraints, sacrificing the accuracy of results. In this work, we consider a generalization of the classical packet classification problem. Our major contribution is to introduce various representations for approximate packet classifiers with controlled accuracy and optimization techniques to reduce classifier sizes exploiting this new level of flexibility. We validate our theoretical results with a comprehensive evaluation study.

Item Type: Conference or Workshop Papers (Paper)
Subjects: UNSPECIFIED
Divisions: UNSPECIFIED
Depositing User: Kirill Kogan
Date Deposited: 10 Dec 2018 19:09
Last Modified: 10 Dec 2018 19:09
URI: http://eprints.networks.imdea.org/id/eprint/1913

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